Tactical

Humanity’s history is the story of its machines. From the first spark of fire kindled by ingenuity to the synthetic intelligences that now reflect our own capacities back at us, each invention has extended our agency. Invention promises leverage—a spear hurled further, a wheel rolling smoother, a thought processed in parallel by a collective society. Yet, with every extension of our reach, we have inadvertently deepened our vulnerability. The cosmos has offered no reprieve; it has simply watched as we edge closer to the divine, wielding god-like reason alongside god-like woes. If the gift of fire marked the beginning of our ascent, its light also casts the shadow of Prometheus—the eternal reminder of what it costs to seize power not our own.

In the layered structure of existence, we find a trinity of tensions: cosmos and earth, life and sacrifice, ends and means. Each pair whispers of balance but embodies dissonance. The divine encapsulates the interplay between the infinite vastness above and the finite terrestrial reality below. Life itself, entrusted with Prometheus’s fire, oscillates between boundless creation and an unrelenting Red Queen—a ceaseless evolutionary arms race demanding innovation, lest we be left behind. And perhaps most poignantly, the machine—the child of our aspirations—mediates between means and ends, its impartial logic turning our ambitions into mechanisms that reshape the world even as they redefine humanity.

Fig. 1 In Greek mythology, Prometheus, possibly meaning “forethought”, is one of the Titans and a god of fire. Prometheus is best known for defying the Olympian gods by taking fire from them and giving it to humanity in the form of technology, knowledge and, more generally, civilization. Very reasonable to question his ethics.

Every machine we forge, from the earliest stone spear to the intricacies of artificial intelligence, is imbued with our hopes and flaws. Machines do not dream of gods, yet they make us gods of creation and destruction alike. Specialization, the hallmark of a capitalist society, was meant to multiply achievement, but it has also fragmented meaning. The assembly line does not ask why it turns; it only ensures the turning. And so, we stand, Promethean creators, chained to the consequences of our genius. Without the burden of knowledge—without Prometheus or Christ—we might count ourselves among the blissfully ignorant ecosystem, no wiser than the creatures we share it with. But knowledge, as sacrifice, demands more.

This book is born of those demands. It is a meditation on the layers of perception, agency, and physicality that define our shared existence. It is an inquiry into the delicate interplay of creation and consequence, shadow and light, and the burden and brilliance of invention. Above all, it is a call to remember the cost of fire and to wield it with the humility befitting mortals who dare to dream as gods.

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import numpy as np
import matplotlib.pyplot as plt
import networkx as nx

# Define the neural network structure
def define_layers():
    return {
        'World': ['Cosmos', 'Earth', 'Life', 'Prometheus', 'Means', 'Ends', ],
        'Perception': ['Kingdom'],
        'Agency': ['Goat', 'Sheep'],
        'Generativity': ['Ostilità', 'Convenienza', 'Sympatico'],
        'Physicality': ['Offense', 'Lethality',  'Retreat', 'Immunity', 'Defense']
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['Kingdom'],
        'paleturquoise': ['Ends', 'Sheep', 'Sympatico', 'Defense'],
        'lightgreen': ['Means', 'Convenienza', 'Immunity', 'Retreat', 'Lethality'],
        'lightsalmon': [
            'Prometheus', 'Life', 'Goat',
            'Ostilità', 'Offense'
        ],
    }
    return {node: color for color, nodes in color_map.items() for node in nodes}

# Calculate positions for nodes
def calculate_positions(layer, x_offset):
    y_positions = np.linspace(-len(layer) / 2, len(layer) / 2, len(layer))
    return [(x_offset, y) for y in y_positions]

# Create and visualize the neural network graph
def visualize_nn():
    layers = define_layers()
    colors = assign_colors()
    G = nx.DiGraph()
    pos = {}
    node_colors = []

    # Add nodes and assign positions
    for i, (layer_name, nodes) in enumerate(layers.items()):
        positions = calculate_positions(nodes, x_offset=i * 2)
        for node, position in zip(nodes, positions):
            G.add_node(node, layer=layer_name)
            pos[node] = position
            node_colors.append(colors.get(node, 'lightgray'))  # Default color fallback

    # Add edges (automated for consecutive layers)
    layer_names = list(layers.keys())
    for i in range(len(layer_names) - 1):
        source_layer, target_layer = layer_names[i], layer_names[i + 1]
        for source in layers[source_layer]:
            for target in layers[target_layer]:
                G.add_edge(source, target)

    # Draw the graph
    plt.figure(figsize=(12, 8))
    nx.draw(
        G, pos, with_labels=True, node_color=node_colors, edge_color='gray',
        node_size=3000, font_size=9, connectionstyle="arc3,rad=0.2"
    )
    plt.title("Jesus-Like Figure of Sacrifice, But Gifted Us With a Burden!", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 2 Kynurenine. Now that’s a molecule that asks you to look into the abyss. Looks like Plato had his cave, the Wachowski’s had their matrix, and our Feline has the abyss. Ain’t that somethin’? Meanwhile, the teenage Kevin only has time for life’s little games – not yet as deep, contemplative as a grownup Feline! Prometheus demands progress, Jesus asks us to use our growing payoffs as a platform for charity to prisoners, homeless, and famished. Perhaps its a little self-indulgent to be introspective with the help of indoline derivatives? Thats a question for another day!